agentgrep
Read-only search for local AI agent prompts and opt-in conversations across Codex, Claude Code, Cursor, Gemini, Antigravity, Grok, Pi, OpenCode, and VS Code.
agentgrep provides a CLI and an MCP server over the same discovery + parsing layer:
- A terminal CLI (
agentgrep) with a Textual TUI for interactive browsing of normalized records. - An MCP server (
agentgrep-mcp) that exposes search, discovery, catalog, and validation tools to any client that speaks Model Context Protocol.
Pre-alpha. APIs may change.
Install
$ uvx agentgrep --helpOther install methods (pipx, uv add, pip install) and full setup snippets live in the installer widget on agentgrep.org/cli/.
CLI quickstart
Search fast prompt-history stores — ranked by relevance, deduped, with newest as the stable tie-break:
$ agentgrep search "deploy"Use prompt matches to search selected conversations. Targeted search attempts at most 25 conversations by default and reports approximate coverage:
$ agentgrep search "deploy" --deepSearch prompt records across every readable conversation backend:
$ agentgrep search "deploy" --exhaustiveSearch prompts and conversations together in one explicit deep sweep:
$ agentgrep search "deploy" --exhaustive --scope allPrefer ripgrep-shaped flags? grep mirrors rg / ag against the
same records:
$ agentgrep grep "deploy" --scope conversationsStream JSON so a non-MCP agent or shell pipeline can consume the results:
$ agentgrep find --jsonOpen the read-only Textual explorer, seeded with a query:
$ agentgrep ui "deploy"--json and --ndjson make every command pipe-friendly, and any
search-shaped subcommand takes --ui to hand the same query to the
explorer (e.g. agentgrep grep "deploy" --ui). Agents that don't
speak MCP can drive the CLI directly; see
https://agentgrep.org/cli/ for the per-subcommand reference.
MCP server: quickest setup
In Claude Code:
$ claude mcp add agentgrep -- uvx --from agentgrep agentgrep-mcpFor Claude Desktop / Codex / Cursor / Gemini snippets, see https://agentgrep.org/mcp/.
Library quickstart
from pathlib import Path import agentgrep backends = agentgrep.select_backends() query = agentgrep.SearchQuery( terms=("hello",), scope="prompts", any_term=False, regex=False, case_sensitive=False, agents=agentgrep.AGENT_CHOICES, limit=10, effort="prompt", ) result = agentgrep.run_search_result(Path.home(), query, backends=backends) for record in result.records: print(record.agent, record.title or record.path) print(result.summary.status.state, result.summary.coverage)
Links
- Documentation: https://agentgrep.org/
- Source: https://github.com/tony/agentgrep
- Issues: https://github.com/tony/agentgrep/issues
- Changelog: CHANGES
- License: MIT